Barrchives
How Hightouch Builds RL Agents For Marketing Teams, with Kashish Gupta, Co-CEO at Hightouch
Mar 19, 2025
Kashish Gupta, Co-founder and Co-CEO of Hightouch, discusses the revolutionary impact of AI on marketing. He delves into the rise of Composable CDPs, illustrating how they empower marketers with data democratization. Gupta reveals how reinforcement learning agents optimize campaigns through tailored reward systems and highlights the technical challenges faced in building these AI models. He emphasizes the balance between AI efficiency and the creative input needed from marketers to truly engage customers in an increasingly automated landscape.
41:18
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Quick takeaways
- Reinforcement learning agents optimize marketing by personalizing campaigns based on individual customer histories, enhancing long-term customer engagement.
- The shift to composable CDPs empowers marketers with flexible data utilization and user-friendly tools, fostering innovative and personalized marketing strategies.
Deep dives
Optimization through Reinforcement Learning
Reinforcement learning (RL) agents are designed to optimize marketing by acting as a unique marketer for each individual customer in a database. They utilize comprehensive customer action history to understand the best campaigns to implement based on past engagements. This approach prioritizes long-term customer lifetime value (LTV) rather than immediate conversions, allowing for the support of intermediate actions that lead to eventual transactions. By framing marketing as a sequential learning process, these agents excel at selecting campaigns that gradually guide customers toward a specific goal, such as making repeat purchases.
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